Predicting Soil Temperature from Climate Data and Weather Forecasts

Providing point specific forecasts of soil, surface, and boundary layer environmental parameters is an essential part of the agricultural decision making process. As a practical application of predicting frost out, seed emergence, pesticide applications, irrigation needs, and fall dry down, the High Plains Automated Weather Data System has developed methods for applying a running statistical bias to NCEP and ECMWF generated numerical forecasts for the AWDN network in Nebraska. In this paper we discuss the prediction of the date when optimal soil temperatures are reached (50F for corn). These point forecasts are then provided to the public through a web interface, and assist producers in their decision making process.